大数据技术在企业信息安全管理中的应用
1School of Information and Mechatronic Engineering, Hunan International Economics University, Changsha, 410205, China.
Scientific reports
|January 6, 2025
概括
大数据技术 (BDT) 通过实现实时风险预测来增强企业信息安全 (EIS). 一个新的BDT驱动型号显著提高了安全事件的早期预警准确性和响应速度.
科学领域:
- 信息安全 信息安全
- 大数据分析大数据分析
- 机器学习 机器学习
背景情况:
- 企业信息安全 (EIS) 面临着不断变化的威胁.
- 传统的安全方法在实时风险识别方面扎.
- 大数据技术 (BDT) 为先进的安全解决方案提供了潜力.
研究的目的:
- 探索BDT在EIS中的应用价值.
- 为企业开发一个大数据驱动的风险预测模型.
- 增强企业信息安全保护能力.
主要方法:
- 使用复杂的网络算法和机器学习构建了一个大数据分析系统.
- 雇员特征工程和风险指标提取模型培训.
- 针对各种安全威胁,优化模型预测性能.
主要成果:
- 风险预测模型实现了曲线下的面积为0.95.
- 该模型表现出高预测准确度和差异化能力.
- 在多类风险识别中达到0.87的平均精度.
结论:
- 在EIS风险管理方面,BDT是有效的和可行的.
- 开发的预测模型显著提高了预警准确度和响应速度.
- 为企业信息安全保护提供强有力的技术支持.
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